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چکیده
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This research presents a new analytical prediction model to calculate Manning’s roughness coefficient (n) through utilizing relative submergence (), Shields parameter (), Froude number (), and volumetric sediment concentration parameters. The proposed analytical equation took the form to achieve performance achievements of 16.3% absolute relative error coupled with NA of 0.85 and R2 = 0.88 compared to five benchmarked models including Wu and Wang (J Hydraul Eng 125(12):1309–1312, 1999: ARE = 23.5%) and Deng et al. (J Sediment Res 5:24–29, 2007: R2 = 0.15). The analysis demonstrated that flow Froude number (Fr) maintained (−0.28) the strongest effect which decreased n by 32% when Fr at 1.2 reached supercritical conditions. Sediment concentration at 2000 ppm displayed (−0.10) dominant influence by dropping n by 25%. The model simulation applied with 10,000 iterations showed hydraulic radius (R) was the most responsive variable (total-order Sobol index = 0.50) based on uncertainty analysis through Monte Carlo simulations while Bayesian inference validated a 95% confidence interval spanning from 0.025 to 0.045 for n. When applied to changing bedforms with the parameter the prediction accuracy increased by 15% under conditions of mobile bed movement (θ > 0.06). The calculated models find practical use in adaptive flood prediction and sediment-charged channel constructions which lead to risk cuts of 15–25% in flood scenarios. The presented work combines empirical methods with data-based strategies to improve predictive capabilities for situations involving non-uniform unsteady fluid motions.
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